In this paper we explore the relationship between multivariate data analysis and techniques for graph drawing or graph layout. Although both classes of techniques were created for quite different purposes, we find many common principles and implementations. We start with a discussion of the data analysis techniques, in particular multiple correspondence analysis, multidimensional scaling, parallel coordinate plotting, and seriation. We then discuss parallels in the graph layout literature.

Abstract not found

. A highly interactive, user-friendly object-oriented software package written in LispStat is introduced that performs simple and multiple correspondence analysis, and profile analysis. These three techniques are integrated into a single environment driven by a user-friendly graphical interface that takes advantage of Lisp-Stat's advanced graphical capabilities. Techniques that assess the stability of the solution are also introduced. Some of the features of the package include colored graphics, incremental graph zooming capabilities, manual point separation to determine identities of overlapping points, and stability and fit measures. The features of the package are used to show some interesting trends in a large educational dataset. 1. Introduction Exploratory data analytic techniques have become increasingly popular over the last decade. One of the main reasons for their popularity is that they are primarily intended to reveal features in the data, by producing low dimensio...